An extended GRA method for MCDM with interval-valued triangular fuzzy assessments and unknown weights

► We develops an extended GRA method for solving MCDM problems. ► Some optimization models are established. ► Calculation steps of extended GRA method for MCDM are given. ► An example is shown to verify the developed method. Multiple criteria decision making (MCDM) is the process of ranking the feas...

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Bibliographic Details
Published inComputers & industrial engineering Vol. 61; no. 4; pp. 1336 - 1341
Main Authors Zhang, Shi-fang, Liu, San-yang, Zhai, Ren-he
Format Journal Article
LanguageEnglish
Published New York Elsevier Ltd 01.11.2011
Pergamon Press Inc
Subjects
Criteria
Fuzzy
Fuzzy logic
Fuzzy systems
Grey relational analysis (GRA)
Interval-valued triangular fuzzy number
Linguistics
Mathematical analysis
Mathematical models
Mathematical problems
Multiple criteria decision making
Multiple criteria decision making (MCDM)
Operations research
Optimization
Optimization techniques
Studies
Weight information
Interval-valued triangular fuzzy number
Grey relational analysis (GRA)
Weight information
Multiple criteria decision making (MCDM)
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Summary:► We develops an extended GRA method for solving MCDM problems. ► Some optimization models are established. ► Calculation steps of extended GRA method for MCDM are given. ► An example is shown to verify the developed method. Multiple criteria decision making (MCDM) is the process of ranking the feasible alternatives and selecting the best one by considering multiple criteria. Owing to the complexity, fuzziness and uncertainties of the objective things, the criterion values often take the form of linguistic variables, which can be expressed in interval-valued triangular fuzzy numbers. The purpose of this paper is to develop an extended grey relational analysis (GRA) method for solving MCDM problems with interval-valued triangular fuzzy numbers and unknown information on criterion weights. In order to determine the criterion weights, some optimization models based on the basic idea of traditional GRA method are established. Then, calculation steps of extended GRA method for MCDM are given. Finally, a numerical example is shown to verify the developed method and to demonstrate its practicality and feasibility.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2011.08.008